Hadoop3：MapReduce中实现自定义排序

一、场景描述

以统计号码的流量案例为基础，进行开发。

流量统计结果
在这里插入图片描述
我们现在要对这个数据的总流量进行自定义排序。

二、代码实现

我们要对总流量进行排序，就是对FlowBean中的sumFlow字段进行排序。
所以，我们需要让FlowBean实现WritableComparable接口，并重写compareTo方法。

另外，我们知道，排序是在Shuffle过程进行的，且是在环形缓冲区进行的排序
此处的排序，采用快速排序算法，针对key的索引进行排序，按照字典顺序进行排序。

所以，我们需要在mapper程序中，把FlowBean设置成key，这样，Shuffle阶段，会调用FlowBean的compareTo方法，进行排序。

FlowBean.java

package com.atguigu.mapreduce.writableComparable;import org.apache.hadoop.io.Writable;
import org.apache.hadoop.io.WritableComparable;import java.io.DataInput;
import java.io.DataOutput;
import java.io.IOException;/*** 1、定义类实现writable接口* 2、重写序列化和反序列化方法* 3、重写空参构造* 4、toString方法*/
public class FlowBean implements WritableComparable<FlowBean> {private long upFlow; // 上行流量private long downFlow; // 下行流量private long sumFlow; // 总流量// 空参构造public FlowBean() {}public long getUpFlow() {return upFlow;}public void setUpFlow(long upFlow) {this.upFlow = upFlow;}public long getDownFlow() {return downFlow;}public void setDownFlow(long downFlow) {this.downFlow = downFlow;}public long getSumFlow() {return sumFlow;}public void setSumFlow(long sumFlow) {this.sumFlow = sumFlow;}public void setSumFlow() {this.sumFlow = this.upFlow + this.downFlow;}@Overridepublic void write(DataOutput out) throws IOException {out.writeLong(upFlow);out.writeLong(downFlow);out.writeLong(sumFlow);}@Overridepublic void readFields(DataInput in) throws IOException {this.upFlow = in.readLong();this.downFlow = in.readLong();this.sumFlow = in.readLong();}@Overridepublic String toString() {return upFlow + "\t" + downFlow + "\t" + sumFlow;}@Overridepublic int compareTo(FlowBean o) {// 总流量的倒序排序if (this.sumFlow > o.sumFlow) {return -1;} else if (this.sumFlow < o.sumFlow) {return 1;} else {// 按照上行流量的正序排if (this.upFlow > o.upFlow) {return 1;} else if (this.upFlow < o.upFlow) {return -1;} else {return 0;}}}
}

FlowMapper.java

package com.atguigu.mapreduce.writableComparable;import org.apache.hadoop.io.LongWritable;
import org.apache.hadoop.io.Text;
import org.apache.hadoop.mapreduce.Mapper;import java.io.IOException;public class FlowMapper extends Mapper<LongWritable, Text, FlowBean, Text> {private FlowBean outK = new FlowBean();private Text outV = new Text();@Overrideprotected void map(LongWritable key, Text value, Context context) throws IOException, InterruptedException {// 获取一行String line = value.toString();// 切割String[] split = line.split("\t");// 封装outV.set(split[0]);outK.setUpFlow(Long.parseLong(split[1]));outK.setDownFlow(Long.parseLong(split[2]));outK.setSumFlow();// 写出context.write(outK, outV);}
}